Determination of “Neutral”–“Pain”, “Neutral”–“Pleasure”, and “Pleasure”–“Pain” Affective State Distances by Using AI Image Analysis of Facial Expressions

Hermann Prossinger, Tomás Hladký, Silvia Boschetti, Daniel Říha , Jakub Binter

Publications: Contribution to journalArticlePeer Reviewed

Abstract

(1) Background: In addition to verbalizations, facial expressions advertise one’s affective state. There is an ongoing debate concerning the communicative value of the facial expressions of pain and of pleasure, and to what extent humans can distinguish between these. We introduce a novel method of analysis by replacing human ratings with outputs from image analysis software. (2) Methods: We use image analysis software to extract feature vectors of the facial expressions neutral, pain, and pleasure displayed by 20 actresses. We dimension-reduced these feature vectors, used singular value decomposition to eliminate noise, and then used hierarchical agglomerative clustering to detect patterns. (3) Results: The vector norms for pain–pleasure were rarely less than the distances pain–neutral and pleasure–neutral. The pain–pleasure distances were Weibull-distributed and noise contributed 10% to the signal. The noise-free distances clustered in four clusters and two isolates. (4) Conclusions: AI methods of image recognition are superior to human abilities in distinguishing between facial expressions of pain and pleasure. Statistical methods and hierarchical clustering offer possible explanations as to why humans fail. The reliability of commercial software, which attempts to identify facial expressions of affective states, can be improved by using the results of our analyses.

Original languageEnglish
Article number75
Number of pages12
JournalTechnologies
Volume10
Issue number4
DOIs
Publication statusPublished - Aug 2022

Austrian Fields of Science 2012

  • 106018 Human biology

Keywords

  • affective state expression
  • artificial intelligence
  • autoencoder neural network
  • BDSM videos
  • facial expressions
  • facial pain expression
  • facial pleasure expression
  • hierarchical agglomerative clustering
  • image processing

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